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Image processing ---------------- In this study, we adopted the Laplacian of Gaussian (LoG) filter to filter the noise. This filter was used as the basis for one of the proposed feature extraction methods in the segmentation part. Classification -------------- In our study, a multi-class approach was used for disease and cell counting. In order to verify the accuracy of the classifiers, we have adopted the 5-fold cross-validation in which 70% of the data were used for training and the remaining 30% for testing. The following classifiers were used: Random forest with 5 attributes, Support vector machine with radial basis function kernel, AdaBoost with the linear kernel, Linear discriminant analysis with the linear kernel, k-Nearest neighbor with Euclidean distance, Naive bayes with the linear kernel, Random forest with 10 attributes, and Support vector machine with radial basis function kernel. Author Contributions ==================== N. H. contributed to data collection, research design, data analysis, and manuscript writing. M. D. contributed to data collection, research design, and manuscript writing. A. S. contributed to data collection and manuscript writing. R. L. contributed to research design, data collection, and manuscript writing. **Funding:** This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. **Competing Interests:** The authors have declared that no competing interests exist. {#f1} {#f2} {#f3} {#f4} ![Correlation matrices of the studied measures for (A) Lymphocyte cells, (B) Neutroph

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